cuFFT

This document describes cuFFT, the NVIDIA® CUDA™ Fast Fourier Transform (FFT) product. It consists of two separate libraries: cuFFT and cuFFTW. The cuFFT library is designed to provide high performance on NVIDIA GPUs. The cuFFTW library is provided as a porting tool to enable users of FFTW to start using NVIDIA GPUs with a minimum amount of effort. The FFT is a divide-and-conquer algorithm for efficiently computing discrete Fourier transforms of complex or real-valued data sets. It is one of the most important and widely used numerical algorithms in computational physics and general signal processing. The cuFFT library provides a simple interface for computing FFTs on an NVIDIA GPU, which allows users to quickly leverage the floating-point power and parallelism of the GPU in a highly optimized and tested FFT library. The cuFFT product supports a wide range of FFT inputs and options efficiently on NVIDIA GPUs. This version of the cuFFT library supports the following features: ...


References in zbMATH (referenced in 23 articles )

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  1. Peter J. Christopher, Andrew Kadis, George S. D. Gordon, Timothy D. Wilkinson: HoloGen: An open source toolbox for high-speed hologram generation (2020) arXiv
  2. L. Pistone, M. Onorato: nlchains: A fast and accurate time integration of 1-D nonlinear chains on GPUs (2019) not zbMATH
  3. Ashwin Vishnu Mohanan, Cyrille Bonamy, Pierre Augier: FluidFFT: common API (C++ and Python) for Fast Fourier Transform HPC libraries (2018) arXiv
  4. Antti-Pekka Hynninen, Dmitry I. Lyakh: cuTT: A High-Performance Tensor Transpose Library for CUDA Compatible GPUs (2017) arXiv
  5. Peter Steinbach, Matthias Werner: gearshifft - The FFT Benchmark Suite for Heterogeneous Platforms (2017) arXiv
  6. Schaetz, Sebastian; Voit, Dirk; Frahm, Jens; Uecker, Martin: Accelerated computing in magnetic resonance imaging: real-time imaging using nonlinear inverse reconstruction (2017)
  7. Abramov, Timofeǐ V.: Fast numerical solution of boundary value problems with known Green’s function using cyclic convolution (2016)
  8. Lončar, Vladimir; Balaž, Antun; Bogojević, Aleksandar; Škrbić, Srdjan; Muruganandam, Paulsamy; Adhikari, Sadhan K.: CUDA programs for solving the time-dependent dipolar Gross-Pitaevskii equation in an anisotropic trap (2016)
  9. Pilar Cossio, David Rohr, Fabio Baruffa, Markus Rampp, Volker Lindenstruth, Gerhard Hummer: BioEM: GPU-accelerated computing of Bayesian inference of electron microscopy images (2016) arXiv
  10. D’Amore, L.; Laccetti, G.; Romano, D.; Scotti, G.; Murli, A.: Towards a parallel component in a GPU-CUDA environment: a case study with the L-BFGS Harwell routine (2015)
  11. Einkemmer, Lukas; Ostermann, Alexander: On the error propagation of semi-Lagrange and Fourier methods for advection problems (2015)
  12. Feng, Chunsheng; Shu, Shi; Xu, Jinchao; Zhang, Chen-Song: Numerical study of geometric multigrid methods on CPU-GPU heterogeneous computers (2014)
  13. Leclaire, Sébastien; El-Hachem, Maud; Trépanier, Jean-Yves; Reggio, Marcelo: High order spatial generalization of 2D and 3D isotropic discrete gradient operators with fast evaluation on GPUs (2014)
  14. Yang, Yi; Zhou, Huiyang: A highly efficient FFT using shared-memory multiplexing (2014)
  15. Chen, Yifeng: Algebraic program semantics for supercomputing (2013)
  16. Gai, Jiading; Obeid, Nady; Holtrop, Joseph L.; Wu, Xiao-Long; Lam, Fan; Fu, Maojing; Haldar, Justin P.; Hwu, Wen-mei W.; Liang, Zhi-Pei; Sutton, Bradley P.: More IMPATIENT: a gridding-accelerated Toeplitz-based strategy for non-Cartesian high-resolution 3D MRI on gpus (2013) ioport
  17. Alcaraz-Pelegrina, J. M.; Rodríguez-García, P.: Simulations of pulse propagation in optical fibers using graphics processor units (2011)
  18. Maintz, Stefan; Eck, Bernhard; Dronskowski, Richard: Speeding up plane-wave electronic-structure calculations using graphics-processing units (2011)
  19. Rossinelli, Diego; Bergdorf, Michael; Cottet, Georges-Henri; Koumoutsakos, Petros: GPU accelerated simulations of bluff body flows using vortex particle methods (2010)
  20. Ruiz, Antonio; Ujaldon, Manuel; Cooper, Lee; Huang, Kun: Non-rigid registration for large sets of microscopic images on graphics processors (2009) ioport

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